Artificial Intelligence based 5G Coverage Design and optimization using Deep Generative Adversarial Neural Networks

Modern 5G networks require complete rethinking of the network management and self-organizing functionality in order to provide extremely high quality of user experience across multi-tier coverage with different cells radius. In this paper, we propose a novel approach for the small cells coverage planning and performance optimization for multi-tier heterogeneous network based on the artificial intelligence (AI). We develop the AI plane in a way that knowledge is derived there and delivered to the each local SDN controller in a simplified form. Proposed approach allows to effectively train deep neural networks by using generative adversarial networks (GAN) for various topologies in conditions of limited amount of real data about network behavior and performance.